WO2021011759A1 - Procédés d'analyse de composants de pétrole brut à l'aide d'une détection de diffusion de lumière par évaporation - Google Patents

Procédés d'analyse de composants de pétrole brut à l'aide d'une détection de diffusion de lumière par évaporation Download PDF

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Publication number
WO2021011759A1
WO2021011759A1 PCT/US2020/042301 US2020042301W WO2021011759A1 WO 2021011759 A1 WO2021011759 A1 WO 2021011759A1 US 2020042301 W US2020042301 W US 2020042301W WO 2021011759 A1 WO2021011759 A1 WO 2021011759A1
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crude oil
detector
fraction
detector output
asphaltenes
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PCT/US2020/042301
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English (en)
Inventor
Jonathan D. WEBB
Nadjiib BOUSSAD
Stephanie R. STA MARIA
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Exxonmobil Research And Engineering Company
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Publication of WO2021011759A1 publication Critical patent/WO2021011759A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02—Column chromatography
    • G01N30/62—Detectors specially adapted therefor
    • G01N30/78—Detectors specially adapted therefor using more than one detector
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02—Column chromatography
    • G01N30/88—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
    • G01N2030/8809—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 analysis specially adapted for the sample
    • G01N2030/884—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 analysis specially adapted for the sample organic compounds
    • G01N2030/8854—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 analysis specially adapted for the sample organic compounds involving hydrocarbons
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02—Column chromatography
    • G01N30/62—Detectors specially adapted therefor
    • G01N30/74—Optical detectors
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02—Column chromatography
    • G01N30/86—Signal analysis

Definitions

  • the present disclosure relates to analyses of crude oil or crude oil components and process controls relating to such analyses.
  • compositional changes within a crude oil may occur during transport of the crude oil through a pipeline or via rail.
  • compositional analyses conducted in the oilfield may not be overly sophisticated and may be subject to a variety of operator or instrumentation errors. Incorrect compositional analyses can lead to production upsets and/or off-specification products being obtained during refining if an off-specification crude oil is not identified prior to entering a refining stream.
  • the present disclosure provides dual detection methods for analyzing crude oil.
  • the methods comprise: separating a sample of a crude oil or a component thereof into one or more crude oil fractions using liquid chromatography; assaying at least a portion of the one or more crude oil fractions using a first detector and a second detector, the first detector and the second detector employing different detection techniques; obtaining a first detector output from the first detector and a second detector output from the second detector, the first detector output and the second detector output being associated with the one or more crude oil fractions; determining a relationship between the first detector output and the second detector output; and correlating the relationship between the first detector output and the second detector output to classify the crude oil or the component thereof according to one or more property classifications.
  • dual detection methods for analyzing crude oil may comprise: separating a sample of a crude oil or a component thereof into at least an asphaltenes fraction using a high-pressure liquid chromatography system; assaying the asphaltenes fraction using an evaporative light scattering detector and a photometric detector; obtaining a second detector output associated with the asphaltenes fraction from the evaporative light scattering detector and a first detector output associated with the asphaltenes fraction from the photometric detector; determining a relationship between the first detector output and the second detector output; correlating the relationship between the first detector output and the second detector output to classify the crude oil or the component thereof according to one or more property classifications; and determining, based upon the one or more property classifications, at least one of i) whether the crude oil is suitable for a refining operation, ii) how much of the crude oil should be supplied to a refining operation, or iii) how the refining operation should be modified to accommodate the crude oil.
  • the present disclosure provides methods for analyzing crude oil or a component thereof using a detection ratio.
  • the methods comprise: separating a sample of a crude oil or a component thereof into at least an asphaltenes fraction using liquid chromatography; wherein the asphaltenes fraction comprises a first sub-fraction and a second sub-fraction that are obtained in different elution solvents; assaying the first sub-fraction and the second sub-fraction using an evaporative light scattering detector; obtaining a first detector output associated with the first sub-fraction and a second detector output associated with the second sub-fraction; calculating a detection ratio of the first detector output to the second detector output; determining a relationship between the detection ratio and a third detector output associated with an entirety of the asphaltenes fraction; and correlating the relationship between the detection ratio and the third detector output to classify the crude oil or the component thereof according to one or more property classifications.
  • FIGS.1A, 1B and 2 show plots of evaporative light scattering detection (ELSD) versus variable wavelength detection (VWD) detector outputs for the asphaltenes fractions of multiple HPLC-separated vacuum residues of conventional crude oil samples having low bitumen and multiple HPLC-separated vacuum residues of bitumen-rich crude oil from Athabasca bitumens.
  • the vacuum residues had cut points of 350 o C and 600 o C.
  • FIGS. 3A-3C and 4 show plots of ELSD versus VWD detector outputs for the asphaltenes fractions of multiple HPLC-separated vacuum residues of crude oil samples containing variable amounts of sulfur.
  • the vacuum residue were the 350 o C-600 o C distillation cut of the crude oil, and the sulfur content was calculated at a fixed distillation temperature (1050 o F) based on the sulfur content of the crude oil.
  • FIG. 5 shows a plot of ELSD output (toluene fraction):ELSD output (cyclohexane fraction) versus the ELSD output associated with total asphaltenes for vacuum residues of multiple petroleum samples, some being conventional crude oil samples containing low bitumen and others being bitumen-rich.
  • FIG.6 shows a plot of the ratio of the ELSD detector outputs for the toluene asphaltenes fraction to the cyclohexane asphaltenes fraction for vacuum residues of various crude oil samples, some containing various amounts of asphaltenes and others not containing significant amounts of asphaltenes, both before and after conducting a paraffinic froth treatment.
  • FIGS.7 and 8 show plots of crude oil performance grade against the ratio of the ELSD detector outputs for the toluene asphaltenes fraction to the cyclohexane asphaltenes fraction for vacuum residues of various crude oil samples.
  • the data points in the plots represent the Low Temperature Performance Grade of Asphalt as measured according to the SUPERPAVE ASHTO M320 specification system.
  • the High Temperature Performance Grade of Asphalt was fixed at 64 o C in the plots.
  • FIG.9 shows a plot of ELSD detector output (toluene fraction):ELSD detector output (cyclohexane fraction) versus the ELSD detector output associated with total asphaltenes for vacuum residues of multiple petroleum samples containing variable amounts of sulfur.
  • the present disclosure generally relates to crude oil analyses, especially property determination based upon nonvolatile components of crude oils, and process controls relating to such analyses.
  • the present disclosure provides advantageous analyses that may be conducted relatively quickly, either at a refining site or at other points during transport of a crude oil to a refining site or alternative location.
  • Crude oil components such as vacuum residue may be analyzed to classify the crude oil or crude oil component according to one or more property classifications in some cases.
  • properties such as a bitumen content or a sulfur content of the crude oil or crude oil component may be determined.
  • the analyses disclosed herein are readily applicable to the non-volatile components of crude oil, such as asphaltenes, vacuum residue, bitumen and the like, which can allow a crude oil to be characterized in specific ways. As such, the analyses disclosed herein can allow more effective product formation to be realized when refining crude oils.
  • the present disclosure provides analyses that are based upon liquid chromatographic separation of a crude oil sample or a component thereof, particularly into one or more various non-volatile components.
  • high-pressure liquid chromatography HPLC
  • asphaltenes alone may be separated from a crude oil sample or the component thereof in order to realize the benefits described further herein.
  • analyses according to the disclosure herein may be performed in a few hours or less, which may minimize supply disruptions to a refining operation and/or provide sufficient lead time for modifying a refining operation or other processing operation to accommodate an incoming off-specification crude oil.
  • Crude oil components obtained from a refinery such as vacuum residue or column bottoms, for example, may be advantageously analyzed without additional sample preparation in the analyses discussed herein.
  • non-volatile crude oil components may be analyzed chromatographically to provide one or more quality measures that may otherwise be difficult to determine for a crude oil or a component thereof.
  • one or two detectors may be utilized to analyze chromatographic fractions containing asphaltenes (e.g., obtained during HPLC separation).
  • At least evaporative light scattering detection (ELSD) may be used in the methods disclosed herein.
  • ELSD is used to determine the mass fraction of a dissolved analyte in a given chromatographic eluent. Any analyte that is less volatile (more non-volatile) than the chromatographic solvent may be assayed by ELSD.
  • HPLC fractions containing asphaltenes obtained from a crude oil sample or component thereof may be analyzed using ELSD, with the detector output being processed in various manners described further below to provide one or more measures of product quality for the crude oil.
  • ELSD may be used in combination with a second type of detector, namely a photometric detector, which may employ variable wavelength detection (VWD) in particular instances.
  • VWD variable wavelength detection
  • the detector output from ELSD and the detector output from VWD may be correlatable with one another to provide one or more measures of product quality for a crude oil or a crude oil component.
  • correlation of the relationship between the detector output from ELSD and the detector output from VWD may allow the crude oil or the crude oil component as belonging to one or more property classifications, such as a particular bitumen content and/or a particular sulfur content.
  • Parameters associated with an unknown crude oil sample may be compared against those for a sufficient number of crude oil samples having known properties in order to afford one or more property classifications according to the disclosure herein.
  • the new numbering scheme for groups of the Periodic Table is used.
  • the groups (columns) are numbered sequentially from left to right from 1 through 18, excluding the f-block elements (lanthanides and actinides).
  • sample refers to a portion of a larger collection or volume that is obtained for purposes of analysis.
  • Crude oil refers to a hydrocarbon material that is directly obtained from a subterranean source and may be refined into one or more separated components.
  • Crude oil component refers to a non-volatile component of crude oil that may be obtained from a refining or processing operation.
  • crude oil fraction refers to one or more substances separated from a crude oil or crude oil component by liquid chromatography.
  • ELSD refers synonymously herein to evaporative light scattering detection or an evaporative light scattering detector.
  • VWD refers synonymously herein to variable wavelength detection or a variable wavelength detector.
  • Crude oil analyses of the present disclosure may employ two different detection techniques. Certain methods of the present disclosure may comprise: separating a sample of a crude oil or a component thereof into one or more crude oil fractions using liquid chromatography; assaying at least a portion of the one or more crude oil fractions using a first detector and a second detector, the first detector and the second detector employing different detection techniques; obtaining a first detector output from the first detector and a second detector output from the second detector, the first detector output and the second detector output being associated with the one or more crude oil fractions; determining a relationship between the first detector output and the second detector output; and correlating the relationship between the first detector output and the second detector output to classify the crude oil or the component thereof according to one or more property classifications.
  • the type of liquid chromatography used to separate the crude oil or crude oil component into the one or more crude oil fractions according to the present disclosure may be high-pressure liquid chromatography (HPLC), which also may be referred to in some instances as high-performance liquid chromatography.
  • HPLC high-pressure liquid chromatography
  • Suitable techniques and equipment associated with performing HPLC will be familiar to one having ordinary skill in the art.
  • Particular HPLC techniques and equipment for separating and analyzing crude oil fractions, particularly asphaltenes, are described in more detail hereinbelow.
  • the liquid chromatographic separation associated with the methods of the present disclosure may be accomplished using a high-pressure liquid chromatography system that is capable of separating at least one fraction from a sample of a crude oil or a processed crude oil, namely a non-volatile crude oil component.
  • Processed crude oils include those that have undergone a treatment prior to being fully refined (e.g., a paraffinic froth treatment to remove certain asphaltenes to make the crude oil suitable for transport in a pipeline).
  • at least an asphaltenes fraction may be separated from a crude oil sample or a component thereof using an HPLC system.
  • methods of the present disclosure may utilize an HPLC system employing four columns: a first column for separating asphaltenes, a second column for separating aromatics, and a third column and a fourth column for separating aromatics and resins.
  • the resins and aromatics separated by the third and fourth columns may be eluted under reversed flow conditions. Saturates and naphthene saturates elute through the system of four columns and are eluted first from the HPLC system, followed by asphaltenes, aromatics, and aromatics/resins (under reversed flow conditions).
  • Particular crude oil components that may undergo analysis according to the disclosure herein include, for example, bottoms fractions, asphaltenes, bitumen, diluted bitumen, vacuum residue, and any combination thereof.
  • the second detector may be an evaporative light scattering detector and the first detector may be a photometric detector.
  • the HPLC equipment may be configured such that the HPLC eluent encounters the photometric detector prior to encountering the evaporative light scattering detector.
  • Suitable photometric detectors may be capable of detecting an analyte based upon analysis of one or more wavelengths of electromagnetic radiation.
  • the electromagnetic radiation used for analysis may be ultraviolet electromagnetic radiation, visible electromagnetic radiation, or any combination thereof.
  • the photometric detector may employ a single wavelength of electromagnetic radiation for analyte detection, or multiple wavelengths of electromagnetic radiation may be used.
  • the wavelength(s) of electromagnetic radiation employed for analyte detection using the photometric detector may be fixed by the detector design or the wavelengths may be varied in some detector configurations.
  • a suitable photometric detector may be a variable wavelength detector that is capable of analyzing the analyte at two or more different wavelengths depending on particular application needs. Even when a variable wavelength detector is employed, analyses may be based upon a single wavelength, however.
  • a photodiode array detector may be a suitable variable wavelength detector in particular instances.
  • the methods of the present disclosure may be further extended to determine various parameters associated with a processing operation, such as a refining operation.
  • the methods of the present disclosure may comprise supplying the crude oil or component thereof to a processing operation; and determining, based upon the one or more property classifications associated with the crude oil or component thereof (e.g., bitumen content, sulfur content, or any combination thereof), at least one of i) whether the crude oil is suitable for the processing operation, ii) how much of the crude oil should be supplied to the processing operation, or iii) how the processing operation should be modified to accommodate the crude oil. Determination of these parameters may be based upon an existing refining process model or a modified refining process model designed to accommodate an off-specification crude oil or component thereof.
  • the present disclosure allows various decisions to be made concerning how a crude oil or component thereof is further handled during a processing operation, such as a refining operation. That is, by determining at least one property classification of the crude oil or crude oil component through comparison to known crude oil samples according to the disclosure herein, one may determine if the crude oil or crude oil component is within specification for the processing operation or off-specification in some manner. If the crude oil or crude oil component is suitable for the processing operation, the crude oil or crude oil component may be introduced into the processing operation under established parameters for the processing operation (e.g., based upon established refining process modelling).
  • the crude oil or crude oil component is off-specification and deemed unsuitable for the processing operation, however, one may need to hold the crude oil until it can be determined how the crude oil can be best handled by the processing operation, if it indeed can at all. If the crude oil or crude oil component is off-specification, one may construct a suitable refining process model to determine how much of the crude oil or crude oil component should be supplied to the processing operation and/or how the processing operation should be modified to accommodate the crude oil or crude oil component. For example, an off-specification crude oil may be blended with a different crude oil having a composition suitable to place the aggregate blend within specification. A detailed discussion of how to construct a refining process model is beyond the scope of this disclosure.
  • Properties of a crude oil or crude oil component that may be classified using the methods of the present disclosure include, for example, a type of the crude oil, particularly a bitumen content of the crude oil, a sulfur content of the crude oil, and any combination thereof.
  • the foregoing properties may particularly be determined by analyzing an asphaltenes fraction that is further chromatographically separated from the sample of the crude oil or crude oil component.
  • Analyses to classify a crude oil or component thereof according to one or more property classifications may comprise measuring a detector response for at least two samples of a crude oil sample having an unknown composition, performing linear regression of the detector response(s) for the at least two samples of the crude oil sample, and comparing the slope and y-intercept obtained from the linear regression against a predetermined range of values for crude oil samples having a known composition, as described further herein. Comparison of the slope and y-intercept of the crude oil sample having the unknown composition against those of the crude oil samples having known compositions may allow the crude oil or component thereof to be categorized accordingly.
  • determining a relationship between the first detector output and the second detector output may involve measuring whether there is a linear variation between the second detector output (e.g., the evaporative light scattering detector output) and the first detector output (e.g., the photometric detector output at a particular detection wavelength).
  • Such linear variation between the first detector output and the second detector output particularly when analyzing an asphaltenes fraction of a crude oil sample, may allow one to determine the identity (composition or type of crude oil, particularly whether the crude oil is bitumen-rich or bitumen poor), a sulfur content of the crude oil, or any combination thereof.
  • Analysis of a sample of an unknown crude oil may be conducted by comparing the first and second detector outputs of the unknown crude oil or crude oil component to previously analyzed crude oil samples having known properties. That is, parametric fitting of the crude oil sample having an unknown composition may be conducted based upon linear regression analyses. It is to be appreciated that the relationship between the first detector output and the second detector output may vary non-linearly in some instances, and data fitting protocols other than a linear regression analysis may be performed. For example, the relationship between the first detector output and the second detector output may be fit by a power function, an exponential function, a logarithmic function, or the like.
  • more particular methods of the present disclosure may comprise: separating a sample of a crude oil or a component thereof into at least an asphaltenes fraction using a high-pressure liquid chromatography system; assaying the asphaltenes fraction using an evaporative light scattering detector and a photometric detector; obtaining a second detector output associated with the asphaltenes fraction from the evaporative light scattering detector and a first detector output associated with the asphaltenes fraction from the photometric detector; determining a relationship between the first detector output and the second detector output; correlating the relationship between the first detector output and the second detector output to classify the crude oil or the component thereof according to one or more property classification; and determining, based upon the one or more property classifications associated with the crude oil or the component thereof, at least one of i) whether the crude oil is suitable for a refining operation, ii) how much of the crude oil should be supplied to a refining operation, or iii) how the refining operation should be modified to accommodate
  • the property of the crude oil or crude oil component may also be determined by using a single detector and analyzing particular sub-fractions obtained from the liquid chromatography separation.
  • a first sub-fraction and a second sub-fraction of the asphaltenes may be analyzed by evaporative light scattering detection to classify the crude oil or component thereof according to one or more property classifications, such as to determine the identity (composition or type of crude oil), a sulfur content of the crude oil, or any combination thereof.
  • the foregoing property classifications may be conducted independently of those made using evaporative light scattering detection and photometric detection in combination with one another, or they may be made concurrently with such analyses.
  • analyses conducted using evaporative light scattering detection alone may be used to determine the accuracy of analyses made using both evaporative light scattering detection and photometric detection.
  • HPLC systems suitable for conducting analyses using evaporative light scattering detection alone may employ solely ELSD detection or both ELSD and photometric detection techniques.
  • certain methods of the present disclosure may comprise: separating a sample of a crude oil or a component thereof into at least an asphaltenes fraction using liquid chromatography; wherein the asphaltenes fraction comprises a first sub-fraction and a second sub- fraction that are obtained in different elution solvents; assaying the first sub-fraction and the second sub-fraction using an evaporative light scattering detector; obtaining a first detector output associated with the first sub-fraction and a second detector output associated with the second sub- fraction; calculating a detection ratio of the first detector output to the second detector output; determining a relationship between the detection ratio and a third detector output associated with an entirety of the asphaltenes fraction; and correlating the relationship between the detection ratio and the third detector output to classify the crude oil or the component thereof according to one or more property classifications.
  • a first sub-fraction of the asphaltenes fraction may be eluted using the first solvent and a second sub-fraction of the asphaltenes fraction may be eluted using the second solvent.
  • the differing elution properties may result from varying solubility characteristics of the different asphaltenes.
  • the first sub-fraction may comprise a cyclohexane fraction (cyclohexane eluted fraction) of the asphaltenes and the second sub-fraction may comprise a toluene fraction (toluene eluted fraction) of the asphaltenes.
  • analyses employing ELSD alone may be used to drive various decisions during a processing operation, such as a refining operation. That is, by making a property classification and/or determining at least one property of the crude oil or crude oil component according to the disclosure herein, one may determine if the crude oil or crude oil component is within specification for the processing operation or off-specification in some manner.
  • such methods of the present disclosure may further comprise supplying the crude oil or crude oil component to a processing operation; and determining, based upon the one or more property classifications of the crude oil or crude oil component, at least one of i) whether the crude oil is suitable for the processing operation, ii) how much of the crude oil should be supplied to the processing operation, or iii) how the processing operation should be modified to accommodate the crude oil. Determination of these parameters may be based upon an existing refining process model or a modified refining process model designed to accommodate an off-specification crude oil. For example, an off-specification crude oil may be processed according to a modified run plan. Alternately, if a suitable modified run plan cannot be devised, alternative run plans may be implemented to produce a different product from the crude oil or crude oil component.
  • Determining a relationship between the detection ratio using ELSD and the third detector output associated with an entirety of the asphaltenes fraction may involve measuring whether there is a linear variation between the detection ratio and the third detector output.
  • Such linear variation between the detection ratio and the third detector output may allow one to determine the identity (composition or type of crude oil), a sulfur content of the crude oil, or any combination thereof.
  • the linear variation may be used to develop a regression equation for a plurality of crude oils or crude oil components having a known composition.
  • a crude oil or crude oil component having an unknown composition may be assayed at two or more concentrations to determine the slope and y-intercept, which may then be compared to the crude oils or crude oil components having a known composition in order to classify the crude oil or crude oil components according to one or more property classifications.
  • data fitting protocols other than linear regression may be appropriate in some instances.
  • A. Methods for classifying a crude oil or crude oil fraction comprise: separating a sample of a crude oil or a component thereof into one or more crude oil fractions using liquid chromatography; assaying at least a portion of the one or more crude oil fractions using a first detector and a second detector, the first detector and the second detector employing different detection techniques; obtaining a first detector output from the first detector and a second detector output from the second detector, the first detector output and the second detector output being associated with the one or more crude oil fractions; determining a relationship between the first detector output and the second detector output; and correlating the relationship between the first detector output and the second detector output to classify the crude oil or the component thereof according to one or more property classifications.
  • B. Methods for categorizing a crude oil or crude oil fraction by analyzing asphaltenes comprise: separating a sample of a crude oil or a component thereof into at least an asphaltenes fraction using a high-pressure liquid chromatography system; assaying the asphaltenes fraction using an evaporative light scattering detector and a photometric detector; obtaining a second detector output associated with the asphaltenes fraction from the evaporative light scattering detector and a first detector output associated with the asphaltenes fraction from the photometric detector; determining a relationship between the first detector output and the second detector output; correlating the relationship between the first detector output and the second detector output to classify the crude oil or the component thereof according to one or more property classifications; and determining, based upon one or more property classifications, at least one of i) whether the crude oil is suitable for a refining operation, ii) how much of the crude oil should be supplied to a refining operation, or iii) how the refining
  • C. Methods for categorizing a crude oil or crude oil fraction using a detection ratio comprise: separating a sample of a crude oil or a component thereof into at least an asphaltenes fraction using liquid chromatography; wherein the asphaltenes fraction comprises a first sub-fraction and a second sub-fraction that are obtained in different elution solvents; assaying the first sub-fraction and the second sub-fraction using an evaporative light scattering detector; obtaining a first detector output associated with the first sub-fraction and a second detector output associated with the second sub-fraction; calculating a detection ratio of the first detector output to the second detector output; determining a relationship between the detection ratio and a third detector output associated with an entirety of the asphaltenes fraction; and correlating the relationship between the detection ratio and the third detector output to classify the crude oil or the component thereof according to one or more property classifications.
  • Embodiments A-C may have one or more of the following additional elements in any combination:
  • Element 1 wherein the second detector is an evaporative light scattering detector and the first detector is a photometric detector.
  • Element 2 wherein the second detector is an evaporative light scattering detector and the first detector is a variable wavelength detector.
  • Element 3 wherein the one or more crude oil fractions comprise an asphaltenes fraction.
  • Element 4 wherein the method further comprises: supplying the crude oil or the component thereof to a processing operation; and determining, based upon the one or more property classifications, at least one of i) whether the crude oil is suitable for the processing operation, ii) how much of the crude oil should be supplied to the processing operation, or iii) how the processing operation should be modified to accommodate the crude oil.
  • Element 5 wherein the processing operation comprises a refining operation.
  • Element 6 wherein the component of the crude oil is selected from the group consisting of a bottoms fraction, bitumen, diluted bitumen, asphaltenes, vacuum residue, and any combination thereof.
  • Element 7 wherein the one or more property classifications are selected from the group consisting of a type of the crude oil, a sulfur content of the crude oil, and any combination thereof.
  • Element 8 wherein the sample is separated by a high-pressure liquid chromatography system.
  • Element 9 wherein the high-pressure liquid chromatography system employs a first column for separating asphaltenes, a second column for separating aromatics, and a third column and a fourth column for separating aromatics and resins.
  • Element 10 wherein the method further comprises: supplying the crude oil or the component thereof to the refining operation.
  • Element 11 wherein the method further comprises: modifying at least one process parameter associated with the refining operation based upon the one or more property classifications.
  • Element 12 wherein the photometric detector is a variable wavelength detector.
  • Element 13 wherein the first sub-fraction comprises a cyclohexane fraction of the asphaltenes fraction and the second sub-fraction comprises a toluene fraction of the asphaltenes fraction.
  • Element 14 wherein the crude oil or the component thereof has been subjected to a paraffinic froth treatment.
  • exemplary combinations applicable to the method of A include: 1 and 3; 2 and 3; 1 and 4; 2 and 4; 1 and 6; 2 and 6; 1 and 7; 2 and 7; 3 and 7; 4 and 7; 4, 5 and 7; 6 and 7; 1 and 8; 2 and 8; 3 and 8; 4 and 8; 4, 5 and 8; 6 and 8; 7 and 8; 1, 8 and 9; 2, 8 and 9; 3, 8 and 9; 4, 8 and 9; 5, 8 and 9; 6, 8 and 9; and 7-9.
  • Exemplary combinations applicable to B include 10 and 11; 10 and 12; 11 and 12; 7 and 10; 7 and 11; 7 and 12; 7, 10 and 11; 7, 10 and 12; 7, 11 and 12; and 7 and 10-12.
  • Exemplary combinations applicable to C include 7 and 13; 7 and 14; 13 and 14; 7, 13 and 14; 4 and 7; 4 and 13; 4 and 14; 4, 13 and 14; 4 and 5; and 4, 5 and 7.
  • the HPLC was equipped with VWD (500 nm, 4000 mAU attenuation) and ELSD (30°C Nebulizer, 60°C Evaporator, 1.6 SLM Nitrogen Flow, 7% LED Intensity) for detection of the solvent fractions. No additional purification was applied to commercially purchased solvents or stationary phases.
  • the solvents for sample preparation and HPLC separation (heptane, cyclohexane, toluene, methylene chloride, methanol and chlorobenzene) were purchased from Sigma Aldrich as HPLC grade.
  • the stationary phases for the HPLC columns were acquired from Western Research Institute (PFTE) and Sigma Aldrich (glass beads, 150-212 mm; aminopropyl silica, 1 mmol/g NH 2 ; 40-63 mm; and silica gel, Davisil 62, 60-200 Mesh). The columns were packed according to standard protocols and thermostated to 30°C. A quality control sample was measured every 8 samples to ensure response stability from the instrument. [0066] 20 ⁇ L of a 10 wt. % solution of petroleum residue (200 mg in 2 mL of chlorobenzene, dissolved with periodic shaking) was injected into the 4-column HPLC unit, described above, which was equilibrated with heptane at 30 o C.
  • PFTE Western Research Institute
  • Sigma Aldrich glass beads, 150-212 mm; aminopropyl silica, 1 mmol/g NH 2 ; 40-63 mm; and silica gel, Davisil 62, 60-200 Mesh.
  • distillation of the petroleum sample or petroleum residue may be performed to provide a 400 o C+ cut point.
  • the sample was passed through columns that were sequentially packed with the PTFE, glass beads, aminopropyl silica and silica gel. The flow rate was 2.0 mL/min. The representative pressure range for the separation sequence was 10-25 bar.
  • the solvent fractions were detected in the order of saturates, naphthene saturates, cyclohexane asphaltenes, toluene asphaltenes, methylene chloride : methanol (98:2) asphaltenes, aromatics 1, aromatics 2 and resins by varying solvents and by performing column switching.
  • the resulting chromatograms were integrated based upon the detector output of two different detectors: an evaporative light scattering detector (ELSD) and a variable wavelength detector (VWD) operating at 500 nm.
  • ELSD evaporative light scattering detector
  • VWD variable wavelength detector
  • a single-column HPLC may be used to collect asphaltenes for analysis using cyclohexane and toluene eluents, with detection and integration being conducted as above.
  • the VWD may also be operated at other wavelengths, such as 280 or 340 nm and/or the injected solution may range from 4-20% in concentration.
  • FIGS.1A, 1B and 2 show plots of ELSD versus VWD detector outputs for the asphaltenes fractions of multiple HPLC-separated conventional crude oil samples (low bitumen) and multiple HPLC-separated bitumen-rich crude oil samples.
  • the plots contain data for 201 vacuum residue samples (350 o C to 600 o C) obtained from 51 crude oils and bitumens in total, which were obtained from a variety of global locations.
  • FIGS.1A and 2A there was roughly a linear correlation between the detector outputs for the conventional crude oil samples and for the bitumen-rich samples, such that the two types of petroleum are readily distinguishable in a statistically significant manner from one another in the plots.
  • FIG.1B shows the corresponding plot for only the bitumen-rich samples from FIG. 1A, with the regression equation provided as well.
  • FIGS.1A and 1B show the correlation between the cyclohexane asphaltenes fractions.
  • FIG. 2 shows the correlation between the toluene asphaltenes fractions.
  • obtaining the detector outputs for an unknown crude oil sample may allow the type of the crude oil to be determined by fitting (correlating) the detector outputs to the known samples.
  • the crude oil or crude oil component was dissolved in chlorobenzene at a minimum of two different concentrations, such as 5 wt. % and 10 wt. %.
  • the samples were then separated by HPLC as above, and the detector outputs were compared to the known samples.
  • the slope and y-intercept of the asphaltenes peak of the unknown crude oil or crude oil component were then calculated using Equations 1 and 2 below,
  • m is the slope
  • b is the y-intercept
  • y1 and y2 are the ELSD integrated detector outputs at the two concentrations
  • x 1 and x 2 are the VWD integrated detector outputs at the two concentrations.
  • the slope and y-intercept of the unknown crude oil or crude oil component can then be compared to that of the known samples in order to classify the crude oil as containing a particular amount of bitumen. Further details concerning the classification of a crude oil or crude oil component based on Equations 1 and 2 is provided below.
  • FIGS. 3A-3C and 4 show plots of ELSD versus VWD detector outputs for the asphaltenes fractions of multiple HPLC-separated crude oil samples containing variable amounts of sulfur.
  • the sulfur content was calculated at a fixed distillation temperature (1050 o F) based upon the sulfur content of the corresponding crude oil.
  • the samples analyzed in FIGS.3A-3C and 4 were vacuum residues representing a 350 o C-600 o C distillation cut of the corresponding crude oil. Samples were classified as containing less than 4 wt. % sulfur, 4- 5 wt. % sulfur, or greater than 5 wt. % sulfur.
  • FIGS.3A and 4 there was roughly a linear correlation between the detector outputs for each class of sulfur-containing crude oils, such that each class is readily distinguishable in a statistically significant manner from the other classes in the plots.
  • FIG.3A shows the correlation between the cyclohexane asphaltenes fractions.
  • FIG. 3B shows the corresponding plot for only the samples from FIG.3A containing greater than 5 wt. % sulfur, with the regression equation provided as well.
  • FIG.3C shows the corresponding plot for only the samples from FIG. 3A containing less than 5 wt. % sulfur (including samples from the sub-categories 4-5 wt. % sulfur and less than 4 wt. % sulfur), with the regression equation provided as well.
  • FIG.4 shows the correlation between the toluene asphaltenes fractions.
  • obtaining the detector outputs for an unknown sulfur-containing crude oil sample may allow the amount of sulfur in the crude oil sample to be broadly characterized by fitting (correlating) the detector outputs to the known samples.
  • the crude oil or crude oil component was dissolved in chlorobenzene at a minimum of two different concentrations, such as 5 wt. % and 10 wt. %.
  • the samples were then separated by HPLC as above, and the detector outputs were compared to the known samples.
  • the slope and y-intercept of the asphaltenes peak of the unknown crude oil or crude oil component were then calculated using Equations 1 and 2.
  • the slope and y-intercept of the unknown crude oil or crude oil component can then be compared to that of the known samples in order to classify the crude oil as containing a particular amount of sulfur. Further details concerning the classification of a crude oil or crude oil component based on Equations 1 and 2 is provided below.
  • the calculated slope and y-intercept can be used to simultaneously classify an unknown crude oil or crude oil component as being bitumen-containing or non-bitumen-containing (conventional crude oil) and to provide an assessment of the relative amount of sulfur in the sample.
  • the calculated slope may be used to distinguish 1) bitumen-containing crude oil or crude oil components and crude oil or crude oil components containing greater than 5 wt. % sulfur from 2) crude oil or crude oil components containing less than 5 wt. % sulfur.
  • the calculated y-intercept may be used to distinguish bitumen-containing crude oils or crude oil components from those that contain greater than 5 wt. % sulfur.
  • Table 1 summarizes the slope and y-intercept parameters from the regression equations shown in FIGS.1B, 3B and 3C, which were obtained for vacuum residue samples.
  • bits containing less than 5 wt. % sulfur exhibited a slope that is distinguishable from samples containing bitumen or samples containing greater than 5 wt. % sulfur.
  • Bitumen-containing samples in turn, can be distinguished from both types of sulfur-containing samples on the basis of the positive y-intercepts exhibited by bitumen-containing samples.
  • An appropriate confidence interval may be utilized when analyzing the slope and y- intercept of a sample of a given crude oil or crude oil component.
  • Appropriate confidence intervals may vary from application to application, such as based upon potential risk to operations.
  • the slope and y-intercept may range from two times the standard error coefficient obtained from the regression equations. Table 2 below summarizes the standard error coefficients for slope and y-intercept and the corresponding 95% confidence intervals for slope and y-intercept for the three types of samples. Table 2
  • Secondary analyses such as density measurements or gas chromatography analyses may be performed in order to distinguish between bitumen- containing and sulfur-containing crude oils or crude oil components, in the event that a satisfactory determination cannot be made according to the disclosure herein.
  • Production calculations may also be performed to determine the consequences of processing a crude oil type other than that expected, and if the crude oil cannot be satisfactorily processed, changes to the production plan may be implemented.
  • the linear regression analyses may also be performed using different sample concentrations of the unknown crude oil or crude oil component to determine the fidelity of the initial measurements (e.g., those made at 5 wt. % and 10 wt. %). Alternately, samples having the initial concentration may be retested and the results averaged. Although measuring additional sample concentrations or additional replicates of the same sample concentration may not resolve the measurement uncertainty, it may aid in improving confidence of the fidelity of the sample identification.
  • HPLC analyses were conducted as in Example 1, except only the asphaltenes fractions were collected for analysis and only the ELSD detector output was analyzed. The cyclohexane asphaltenes fractions and the toluene asphaltenes fractions were analyzed further, as described hereinafter.
  • FIG. 5 shows a plot of ELSD output (toluene fraction):ELSD output (cyclohexane fraction) versus the ELSD output associated with total asphaltenes for multiple petroleum samples, some being conventional crude oil samples containing low bitumen and others being bitumen-rich.
  • obtaining the ELSD output for the asphaltenes fractions of an unknown crude oil sample may allow the type of the crude oil to be determined by fitting (correlating) the detector output to the known samples.
  • Paraffinic froth treatments selectively remove toluene-soluble asphaltenes from a petroleum sample in deference to cyclohexane-soluble asphaltenes. This process may be used to improve the quality of a petroleum product and the facilitate pipeline transport thereof.
  • the outcome of conducting a PFT on a petroleum product may be determined by plotting the ratio of the ELSD outputs of the toluene asphaltenes fraction to the cyclohexane asphaltenes fraction. Values residing lower on the y-axis are distinctive of the decreased toluene-soluble asphaltene content afforded by removing this component of the petroleum product. Therefore, lower y-axis values are distinctive of a different product quality.
  • FIG.6 shows a plot of the ratio of the ELSD outputs for the toluene asphaltenes fraction to the cyclohexane asphaltenes fraction for various crude oil samples, some containing various amounts of asphaltenes and others not containing significant amounts of asphaltenes.
  • the effect on the ratio of conducting a paraffinic froth treatment on the crude oil samples is also shown.
  • crude oil samples with lower asphaltene contents can be readily identified, particularly those subjected to PFT, as evident from their lower ratios.
  • FIGS. 7 and 8 show plots of crude oil performance grade for vacuum residue samples against the ratio of the ELSD outputs of the toluene asphaltenes fraction to the cyclohexane asphaltenes fraction. As shown, there was a linear correlation between the ratio and performance grade, with lower temperatures representing a higher performance grade. Namely, the plots demonstrate that different amounts of asphaltenes in the vacuum residue samples may be correlated to overall asphalt quality of the vacuum residue.
  • the low temperature performance grade relates to the low temperature cracking susceptibility of an asphalt obtained from the vacuum residue samples when incorporated in an asphalt.
  • the intermediate performance grade specification relates to the fatigue cracking susceptibility of the vacuum residue samples when incorporated in an asphalt. In both cases, lower temperatures are indicative of higher quality material. As shown, minesite PFT material affords a low quality asphalt and whole bitumen affords a higher quality asphalt, as determined in reference to SUPERPAVE ASHTO M320 specifications.
  • FIG.9 shows a plot of ELSD output (toluene fraction):ELSD output (cyclohexane fraction) versus the ELSD output associated with total asphaltenes for multiple petroleum samples containing variable amounts of sulfur.
  • the samples were classified as containing less than 1.5 wt. % sulfur, 1.5-3 wt.
  • obtaining the ELSD output for the asphaltenes fractions of an unknown crude oil sample may allow the amount of sulfur in the crude oil to be determined by fitting (correlating) the detector output to the known samples. Doing so may aid in refinery units and products meeting sulfur specifications.
  • compositions described herein may be free of any component, or composition not expressly recited or disclosed herein. Any method may lack any step not recited or disclosed herein.
  • composition, element, or elements are considered synonymous with the term“including.”
  • transitional phrase“comprising” it is understood that we also contemplate the same composition or group of elements with transitional phrases“consisting essentially of,”“consisting of,”“selected from the group of consisting of,” or“is” preceding the recitation of the composition, element, or elements and vice versa.

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Abstract

Selon l'invention, des échantillons ou des composants de pétrole brut peuvent être séparés par chromatographie en phase liquide pour obtenir une fraction d'asphaltènes qui peut être encore analysée pour classer le pétrole brut selon une ou plusieurs classifications de propriétés, telle que la teneur en soufre ou l'identité chimique. Un échantillon de pétrole brut peut être classé selon une ou plusieurs classifications de propriétés en déterminant une relation entre une première sortie de détecteur et une deuxième sortie de détecteur associée à une ou plusieurs fractions d'un échantillon de pétrole brut ou du composant, telles qu'une fraction d'asphaltènes, et en corrélant la relation avec la ou les classifications de propriétés. En variante, le rapport de la sortie de détecteur pour une sous-fraction de toluène de la fraction d'asphaltènes à la sortie de détecteur pour une sous-fraction de cyclohexane de la fraction d'asphaltènes d'un échantillon ou d'un composant de pétrole brut peut être tracé par rapport à la sortie de détecteur totale pour déterminer la ou les classifications de propriétés.
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EP4303672A1 (fr) * 2022-07-08 2024-01-10 Yokogawa Electric Corporation Appareil de génération de modèle d'évaluation, procédé de génération de modèle d'évaluation et programme de génération de modèle d'évaluation

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EP4303672A1 (fr) * 2022-07-08 2024-01-10 Yokogawa Electric Corporation Appareil de génération de modèle d'évaluation, procédé de génération de modèle d'évaluation et programme de génération de modèle d'évaluation

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